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<b>请注意:</b><br>本书基于 Elasticsearch 2.x 版本，有些内容可能已经过时。
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<span class="breadcrumb-node">游标查询 <em>Scroll</em></span>
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<h2 class="title">
<a id="scroll"></a>游标查询 <em>Scroll</em><a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elasticsearch-cn/elasticsearch-definitive-guide/edit/cn/060_Distributed_Search/20_Scroll.asciidoc">edit</a>
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<p><code class="literal">scroll</code> 查询   可以用来对 Elasticsearch 有效地执行大批量的文档查询，而又不用付出深度分页那种代价。</p>
<p>游标查询允许我们  先做查询初始化，然后再批量地拉取结果。
这有点儿像传统数据库中的 <em>cursor</em>   。</p>
<p>游标查询会取某个时间点的快照数据。 查询初始化之后索引上的任何变化会被它忽略。
它通过保存旧的数据文件来实现这个特性，结果就像保留初始化时的索引 <em>视图</em> 一样。</p>
<p>深度分页的代价根源是结果集全局排序，如果去掉全局排序的特性的话查询结果的成本就会很低。
游标查询用字段 <code class="literal">_doc</code> 来排序。 这个指令让 Elasticsearch 仅仅从还有结果的分片返回下一批结果。</p>
<p>启用游标查询可以通过在查询的时候设置参数 <code class="literal">scroll</code> 的值为我们期望的游标查询的过期时间。
游标查询的过期时间会在每次做查询的时候刷新，所以这个时间只需要足够处理当前批的结果就可以了，而不是处理查询结果的所有文档的所需时间。
这个过期时间的参数很重要，因为保持这个游标查询窗口需要消耗资源，所以我们期望如果不再需要维护这种资源就该早点儿释放掉。
设置这个超时能够让 Elasticsearch 在稍后空闲的时候自动释放这部分资源。</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">GET /old_index/_search?scroll=1m <a id="CO32-1"></a><i class="conum" data-value="1"></i>
{
    "query": { "match_all": {}},
    "sort" : ["_doc"], <a id="CO32-2"></a><i class="conum" data-value="2"></i>
    "size":  1000
}</pre>
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<div class="calloutlist">
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<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO32-1"><i class="conum" data-value="1"></i></a></p>
</td>
<td align="left" valign="top">
<p>保持游标查询窗口一分钟。</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO32-2"><i class="conum" data-value="2"></i></a></p>
</td>
<td align="left" valign="top">
<p>关键字 <code class="literal">_doc</code> 是最有效的排序顺序。</p>
</td>
</tr>
</table>
</div>
<p>这个查询的返回结果包括一个字段 <code class="literal">_scroll_id</code>， 它是一个base64编码的长字符串  。 现在我们能传递字段
<code class="literal">_scroll_id</code> 到 <code class="literal">_search/scroll</code> 查询接口获取下一批结果：</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">GET /_search/scroll
{
    "scroll": "1m", <a id="CO33-1"></a><i class="conum" data-value="1"></i>
    "scroll_id" : "cXVlcnlUaGVuRmV0Y2g7NTsxMDk5NDpkUmpiR2FjOFNhNnlCM1ZDMWpWYnRROzEwOTk1OmRSamJHYWM4U2E2eUIzVkMxalZidFE7MTA5OTM6ZFJqYkdhYzhTYTZ5QjNWQzFqVmJ0UTsxMTE5MDpBVUtwN2lxc1FLZV8yRGVjWlI2QUVBOzEwOTk2OmRSamJHYWM4U2E2eUIzVkMxalZidFE7MDs="
}</pre>
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<p><a href="#CO33-1"><i class="conum" data-value="1"></i></a></p>
</td>
<td align="left" valign="top">
<p>注意再次设置游标查询过期时间为一分钟。</p>
</td>
</tr>
</table>
</div>
<p>这个游标查询返回的下一批结果。
尽管我们指定字段 <code class="literal">size</code> 的值为1000，我们有可能取到超过这个值数量的文档。
   当查询的时候， 字段 <code class="literal">size</code> 作用于单个分片，所以每个批次实际返回的文档数量最大为
 <code class="literal">size * number_of_primary_shards</code> 。</p>
<div class="note admon">
<div class="icon"></div>
<div class="admon_content">
<p>注意游标查询每次返回一个新字段 <code class="literal">_scroll_id</code>。每次我们做下一次游标查询，
 我们必须把前一次查询返回的字段 <code class="literal">_scroll_id</code> 传递进去。 当没有更多的结果返回的时候，我们就处理完所有匹配的文档了。</p>
</div>
</div>
<div class="tip admon">
<div class="icon"></div>
<div class="admon_content">
<p>提示：某些官方的 Elasticsearch 客户端比如
<a href="http://elasticsearch-py.readthedocs.org/en/master/helpers.html#scan" class="ulink" target="_top">Python 客户端</a> 和
<a href="https://metacpan.org/pod/Search::Elasticsearch::Scroll" class="ulink" target="_top">Perl 客户端</a> 提供了这个功能易用的封装。</p>
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